Curriculum
- 4 Sections
- 16 Lessons
- 1 Day
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- Inventory Analytics – Segmentation & Planning Fundamentals4
- 1.1Concepts: Multi-dimensional classification, target stock levels, segmentation for decision-making
- 1.2Keywords: ABC-XYZ, FSN, Velocity Bands, Cost-Service Trade-off, Inventory Stratification
- 1.3Use Case: Classify SKUs using sales variability and contribution to define planning policies
- 1.4Toolkit: Inventory segmentation model (ABC × XYZ matrix + planning action grid)
- Metrics & Visualization for Inventory Health4
- 2.1Key KPIs: Inventory Turnover Ratio, Days of Cover, Fill Rate, Excess/Obsolete %
- 2.2Keywords: Stock Cover Dashboard, Inventory Ageing Heatmap, Shelf-Life at Risk
- 2.3Real-life Insight: Pharma company used shelf-life based age tracking to reduce write-offs by ₹1.2 Cr annually
- 2.4Exercise: Build an interactive inventory health dashboard with actionable metrics
- Analytics for Demand Shaping & Market Responsiveness4
- 3.1Concepts: Using data to align demand with supply via pricing, promotion, and availability
- 3.2Keywords: Lift Modeling, Cannibalization Effect, Elasticity, Cross-SKU Demand Transfer
- 3.3Case: FMCG firm used analytics to shift demand toward surplus SKUs using regional offers
- 3.4Toolkit: Demand shaping lever matrix (pricing, channel, promo, pack-size)
- Advanced Data Tools & Simulations4
- 4.1Tools: Power BI, Tableau, Python/Pandas, Excel Solver, SQL for Inventory Cubes
- 4.2Keywords: What-if Analysis, Safety Stock Simulation, Scenario Planning
- 4.3Exercise: Simulate a demand surge scenario – plan response with replenishment logic, inventory buffer, and promo control
- 4.4Template: Inventory analytics simulator (inputs: demand volatility, lead time, holding cost)
Keywords: ABC-XYZ, FSN, Velocity Bands, Cost-Service Trade-off, Inventory Stratification
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